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Calibration and aggregation1

In: Qualitative Comparative Analysis

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Abstract

Calibration assigns (a degree of) membership to cases in a set. It is a dialogue between knowledge of cases, context and concepts - not a data conversion - to identify a meaningful threshold (crossover point) between qualitatively different cases. This rules out means, averages and percentiles as calibration anchor points. Calibration answers two questions: ‘What does it means to be a case of X?’, which concerns definition. And ‘How do we know a case of X when we see one?’, which concerns measurement. This chapter explains how to calibrate from qualitative and quantitative data. It explains crisp and fuzzy sets and demonstrates how linguistic hedges (e.g., mostly a case of X) identify degrees of membership. The chapter explains why it is logically impossible for cases to have 0.5 membership in a fuzzy set, and discusses a set-analytical approach to aggregation.

Suggested Citation

  • ., 2024. "Calibration and aggregation1," Chapters, in: Qualitative Comparative Analysis, chapter 8, pages 106-132, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:19631_8
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    File URL: https://www.elgaronline.com/doi/10.4337/9781839104527.00013
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